Lag-1 sparing in the attentional blink: Benefits and costs of integrating two events into a single episode

Abstract

When people monitor a visual stream of rapidly presented stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset—the attentional blink. However, if T2 immediately follows T1, performance is often reported being as good as that at long lags—the so-called Lag-1 sparing effect. Two experiments investigated the mechanisms underlying this effect. Experiment 1 showed that, at Lag 1, requiring subjects to correctly report both identity and temporal order of targets produces relatively good performance on T2 but relatively bad performance on T1. Experiment 2 confirmed that subjects often confuse target order at short lags, especially if the two targets are equally easy to discriminate. Results suggest that, if two targets appear in close succession, they compete for attentional resources. If the two competitors are of unequal strength the stronger one is more likely to win and be reported at the expense of the other. If the two are equally strong, however, they will often be integrated into the same attentional episode and thus get both access to attentional resources. But this comes with a cost, as it eliminates information about the targets' temporal order.

Acknowledgements

We wish to thank Tijmen Moerland, Shalu Saini, and Menno van der Woude for collecting the data for Experiment 1, and Mary Potter and an anonymous reviewer for helpful comments on an earlier draft. This research was supported by a grant of the Volkswagen Foundation awarded to BH.

Notes

Note that we do not claim that our discriminability manipulation reflects variations on a single physical scale or dimension. On the contrary, the three types of target differed in a number of respects: White targets were the most intense, the most unique, and the least well masked stimuli (the letter stream was black); black targets were the least intense, the least unique (same colour as letter stream) and best masked stimuli, which, however, were easy to see on the grey background; grey targets, however, were of medium intensity, relatively unique, not well masked, but very similar to the background. However, the results show that this mix of characteristics was successful in creating three conditions of sufficiently differing difficulty and “competitiveness” with respect to the hypothesized race for access to attentional resources. None of our conclusions depend on how these differences were achieved.

Note that although Lag 1 is most strongly affected by our discriminability manipulation the AB-critical period still shows an effect. In other words, making the processing of the targets easier or more difficult has an impact on the size of the AB. This observation is consistent with a number of other studies (Chun & Potter, 1995; Grandison, Ghirardelli, & Egeth, 1997; Seiffert & Di Lollo, 1997, who also provide an overview) but inconsistent with McLaughlin, Shore, and Klein's (2001) failure to find a relation between target difficulty and the AB. This is somewhat paradoxical because McLaughlin et al.'s design can considered to be the most similar to ours in attempting to manipulate the perceptual quality of the targets and avoiding a task switch between them. However, in contrast to the present study, McLaughlin et al. manipulated the discriminability of T1 and of T2 in different experiments and by using the skeletal target–mask–target–mask task version introduced by Duncan, Ward, and Shapiro (1994). In the absence of more systematic research on this issue we are unable to offer an interpretation of how these procedural differences might explain the divergent outcomes. What seems clear, however, is that McLaughlin and colleagues' conclusion that data-limiting difficulty manipulations do not affect the AB is too general.